The proposed research will develop statistical methods for the sequential analysis of hematologic measurements to provide patient-specific reference values that will facilitate the detection and diagnosis of anemia. Automated storage and analysis of the results of serial hematologic studies are now technically feasible with present-day laboratory instruments and devices for data storage and processing. In current practice, physicians mentally compare a laboratory result with previous values and use their clinical judgement to determine the significance of any change. The proposed research is designed to facilitate this process by developing methods to sequentially analyze test results and identify any departure from the past values of an individual patient. While population-based reference ranges are now used to evaluate individual test values, the use of reference values derived from previous studies of an individual patient would provide a more sensitive means of detecting abnormalities, especially in patients with chronic disorders. To demonstrate the clinical utility of this approach, this project will focus on the detection and evaluation of anemia in hemodialysis patients by examination of the hemoglobin concentration, hematocrit, red cell count, mean corpuscular volume and red cell volume distribution. In particular, our preliminary experience suggests that sequential analysis of the red cell volume distribution will provide an early and sensitive indication of micro- or macrocytic erythropoiesis that precedes alterations in the mean corpuscular volume or hemoglobin concentration. The development of statistical methods for deriving patient-specific reference values for this group would make possible automated examination of laboratory data for the hemodialysis unit with rapid and reliable identification of patients whose hematologic measurements have significantly changed from past values. To provide valid statistical methods for deriving patient-specific reference ranges from serial hematologic measurements, this research project will have three specific aims: (1) develop and validate statistical methods for the sequential analysis of individual hematologic measurements to provide patient-specific reference values for the hemoglobin concentration, hematocrit, red cell count, and mean corpuscular volume; (2) develop and validate statistical methods for the sequential analysis of distributions of hematologic measurements to provide patient-specific comparisons for red cell volume distributions; (3) determine the clinical feasibility and utility of using sequential analyses of hematologic measurements for the evaluation of a group of patients with chronic renal failure who are treated with hemodialysis. Although a limited series of laboratory measurements in a specific group of patients has been selected for study in the proposed project, the methods to be derived would be of general applicability. Providing the statistical foundation for the automated review of laboratory data using patient-specific reference values should facilitate evaluation of test results by physicians by making possible early, sensitive and reliable identification of significant changes from the past values of each patient.